Anna K. Abramowicz, Oimahmad Rahmonov, Justyna Ciesielczuk, Monika J. Fabiańska
Burning coal‐waste dumps are a clear example of anthropogenic landforms that can harm the natural environment in post‐mining regions. In the Upper Silesian Coal Basin (USCB), their surface is often irregularly covered with algal crusts, which can accumulate pollutants very well. To determine the toxicity of these biocrusts on burning dumps and evaluate their role in such extreme conditions, mineral and chemical tests were carried out with a particular focus on heavy metals and polycyclic aromatic hydrocarbons (PAHs). Several environmental indices were used, including the geoaccumulation factor, enrichment factor, contamination factor, ecological risk index, and total carcinogenic risk (TCR). The hazard linked to single PAHs and to the group as a whole in biocrusts was examined, with an average concentration of Σ PAHs reaching 3938.40 μg/kg. Heavy metals such as Zn (avg. 4416.7 ppm), Cd (avg. 25.8 ppm), Pb (avg. 1166.5 ppm), Ni (avg. 327.0 ppm), Cu (avg. 1103.8 ppm) and As (avg. 44.1 ppm) showed elevated concentrations. The combined load of heavy metals and PAHs in the biocrusts indicates a serious environmental threat and potential risks to human health. Environmental indices clearly show that the studied dump represents an extremely contaminated environment, with exceptionally high levels of heavy metal enrichment. The TCR results classify all samples within the high‐risk category. The findings highlight the importance of algal communities in the early stages of colonisation, their potential role in stabilising post‐industrial habitats, and novel insights into combined organic and inorganic pollutant loads in biocrusts under extreme conditions.
{"title":"Accumulation of Heavy Metals and PAHs in Algal Crust on Burning Coal‐Waste Dumps: A Case Study From an Extreme Environment","authors":"Anna K. Abramowicz, Oimahmad Rahmonov, Justyna Ciesielczuk, Monika J. Fabiańska","doi":"10.1002/ldr.70359","DOIUrl":"https://doi.org/10.1002/ldr.70359","url":null,"abstract":"Burning coal‐waste dumps are a clear example of anthropogenic landforms that can harm the natural environment in post‐mining regions. In the Upper Silesian Coal Basin (USCB), their surface is often irregularly covered with algal crusts, which can accumulate pollutants very well. To determine the toxicity of these biocrusts on burning dumps and evaluate their role in such extreme conditions, mineral and chemical tests were carried out with a particular focus on heavy metals and polycyclic aromatic hydrocarbons (PAHs). Several environmental indices were used, including the geoaccumulation factor, enrichment factor, contamination factor, ecological risk index, and total carcinogenic risk (TCR). The hazard linked to single PAHs and to the group as a whole in biocrusts was examined, with an average concentration of Σ PAHs reaching 3938.40 μg/kg. Heavy metals such as Zn (avg. 4416.7 ppm), Cd (avg. 25.8 ppm), Pb (avg. 1166.5 ppm), Ni (avg. 327.0 ppm), Cu (avg. 1103.8 ppm) and As (avg. 44.1 ppm) showed elevated concentrations. The combined load of heavy metals and PAHs in the biocrusts indicates a serious environmental threat and potential risks to human health. Environmental indices clearly show that the studied dump represents an extremely contaminated environment, with exceptionally high levels of heavy metal enrichment. The TCR results classify all samples within the high‐risk category. The findings highlight the importance of algal communities in the early stages of colonisation, their potential role in stabilising post‐industrial habitats, and novel insights into combined organic and inorganic pollutant loads in biocrusts under extreme conditions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"3 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tahmina Kausar, Feida Sun, Yao Li, Jinchao Gong, Shijie Zhou, Muhammad Khalid Rafiq, Akash Tariq, Yue Xiu, Linlin Li, Liang Tie, Abraham Allan Degen, Yanfu Bai
Climate‐induced drought is accelerating the degradation of alpine grasslands, which cover 50%–60% of the Qinghai–Tibetan Plateau and provide critical ecosystem services including biodiversity conservation, carbon storage, and forage production. Degradation and recurrent drought events can reduce aboveground biomass by up to 73%, severely impairing soil function and ecosystem stability. This review highlights biochar as a nature‐based solution (NbS) with measurable potential to enhance drought resilience in alpine ecosystems. Empirical evidence demonstrates that biochar increases soil organic carbon by 2.7–10.7 g kg −1 , total nitrogen by 0.24–0.83 g kg −1 , and soil water‐holding capacity by up to 51% in sandy soils (and ~20% in finer‐textured soils), reduces nutrient leaching and maintains fertility under moisture‐limited conditions. Biochar also enhances microbial biomass C and N, enzymatic activity, and microbial diversity (15%–40%), strengthening nutrient cycling and plant stress tolerance. Field trials show a 25%–30% increase in aboveground biomass, while seed germination and soil seed bank viability improve by 20%–40%, facilitating vegetation regeneration and succession. Co‐benefits include stabilization of soil organic carbon pools (10%–30%) and mitigation of greenhouse gas emissions, reinforcing biochar's role in climate adaptation. By simultaneously addressing the physical, chemical, and biological dimensions of drought stress, biochar offers an integrative pathway for grassland restoration. Nonetheless, uncertainties remain regarding optimal feedstocks, application rates, and long‐term ecological interactions. We advocate embedding biochar in restoration policies, aligning with climate adaptation goals, and promoting cross‐sectoral collaboration to enable scalable deployment. Collectively, the evidence positions biochar as a sustainable, science‐based strategy to secure the multifunctionality of alpine grasslands in a rapidly changing climate.
退化和经常性干旱事件可使地上生物量减少高达73%，严重损害土壤功能和生态系统稳定性。这篇综述强调了生物炭作为一种基于自然的解决方案（NbS），在增强高山生态系统的抗旱能力方面具有可测量的潜力。经验证据表明，在沙质土壤中，生物炭可使土壤有机碳增加2.7-10.7 g kg - 1，总氮增加0.24-0.83 g kg - 1，土壤持水量可提高51%（在细质土壤中可提高20%），减少养分淋失，并在水分限制条件下保持肥力。生物炭还能提高微生物生物量C和N、酶活性和微生物多样性（15%-40%），增强养分循环和植物抗逆性。田间试验表明，地上生物量增加25%-30%，种子萌发和土壤种子库活力提高20%-40%，促进植被更新和演替。Co - benefits包括稳定土壤有机碳库（10%-30%）和减缓温室气体排放，加强生物炭在气候适应中的作用。通过同时处理干旱胁迫的物理、化学和生物维度，生物炭为草地恢复提供了一个综合途径。尽管如此，关于最佳原料、应用速率和长期生态相互作用的不确定性仍然存在。我们主张将生物炭纳入恢复政策，与气候适应目标保持一致，并促进跨部门合作，以实现可扩展的部署。总的来说，这些证据表明，生物炭是一种可持续的、以科学为基础的战略，可以在快速变化的气候中确保高山草原的多功能性。
{"title":"Biochar as a Nature‐Based Solution for Sustainable and Drought‐Resilient Grassland Restoration","authors":"Tahmina Kausar, Feida Sun, Yao Li, Jinchao Gong, Shijie Zhou, Muhammad Khalid Rafiq, Akash Tariq, Yue Xiu, Linlin Li, Liang Tie, Abraham Allan Degen, Yanfu Bai","doi":"10.1002/ldr.70336","DOIUrl":"https://doi.org/10.1002/ldr.70336","url":null,"abstract":"Climate‐induced drought is accelerating the degradation of alpine grasslands, which cover 50%–60% of the Qinghai–Tibetan Plateau and provide critical ecosystem services including biodiversity conservation, carbon storage, and forage production. Degradation and recurrent drought events can reduce aboveground biomass by up to 73%, severely impairing soil function and ecosystem stability. This review highlights biochar as a nature‐based solution (NbS) with measurable potential to enhance drought resilience in alpine ecosystems. Empirical evidence demonstrates that biochar increases soil organic carbon by 2.7–10.7 g kg <jats:sup>−1</jats:sup> , total nitrogen by 0.24–0.83 g kg <jats:sup>−1</jats:sup> , and soil water‐holding capacity by up to 51% in sandy soils (and ~20% in finer‐textured soils), reduces nutrient leaching and maintains fertility under moisture‐limited conditions. Biochar also enhances microbial biomass C and N, enzymatic activity, and microbial diversity (15%–40%), strengthening nutrient cycling and plant stress tolerance. Field trials show a 25%–30% increase in aboveground biomass, while seed germination and soil seed bank viability improve by 20%–40%, facilitating vegetation regeneration and succession. Co‐benefits include stabilization of soil organic carbon pools (10%–30%) and mitigation of greenhouse gas emissions, reinforcing biochar's role in climate adaptation. By simultaneously addressing the physical, chemical, and biological dimensions of drought stress, biochar offers an integrative pathway for grassland restoration. Nonetheless, uncertainties remain regarding optimal feedstocks, application rates, and long‐term ecological interactions. We advocate embedding biochar in restoration policies, aligning with climate adaptation goals, and promoting cross‐sectoral collaboration to enable scalable deployment. Collectively, the evidence positions biochar as a sustainable, science‐based strategy to secure the multifunctionality of alpine grasslands in a rapidly changing climate.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"27 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wang Rui, Li Peng, Zhang Peidong, Zheng Xiaofeng, Liang Jichao, Han Jianchun, Cui Zhiwei
The study of mechanisms of gully headcut erosion is crucial for predicting and preventing soil erosion and effectively reducing gully erosion. However, quantitative analysis from multiple perspectives and dimensions of gully morphological characteristics and their evolution patterns is still unclear. This study conducted a series of indoor flushing experiments using gully headcuts of different heights (flow rates of 2, 4, and 6 L min −1 ; gully headcut heights of 5, 10, and 15 cm). Based on DEM and monitoring data, this study utilizes three erosion modes: gully headcut retreat erosion, gully wall widening erosion, and gully bed downcutting erosion, as representative factors for the longitudinal, lateral, and vertical dimensions, respectively. Through these factors, the characteristic patterns of three distinct dominant developmental modes during gully headcut erosion are revealed. The results indicate that: (1) Discharge rate significantly impacts changes in gully length and width, increasing average headcut retreat erosion rates by at least 19.5% and average headcut erosion width by at least 10.4%. Gully headcut height notably affects gully bottom incision depth, reducing average gully bottom elevation by at least 21.0%. (2) The farther away from the top of the slope, the larger the width of the gully caused by the collapse of the gully wall, and the average widths of the collapse on the slope, during the slope and under the slope were 0.9, 1.9, and 3.8 cm, respectively, indicating that the collapse of the slope is more likely to occur under the slope. (3) The slope of the gully bottom increases with the height of the gully headcut. As the discharge increases, the morphology of the gully bottom slope transitions from “convex upwards” to “concave downwards”. (4) In early stages of erosion development, headcut retreat erosion predominates, contributing 53.2%–82.7% of sediment production. In middle and later stages, gully wall expansion and gully bottom erosion and deposition dominate. These research findings provide insights into mechanisms governing gully erosion on loess slopes.
沟顶侵蚀机理研究对于预测和防治土壤侵蚀，有效减少沟顶侵蚀具有重要意义。然而，从多个角度和维度定量分析沟壑形态特征及其演化模式尚不清楚。本研究使用不同高度的沟顶进行了一系列室内冲洗实验（流速分别为2、4和6 L min - 1；沟顶高度分别为5、10和15 cm）。在DEM和监测数据的基础上，采用沟头后退侵蚀、沟壁加宽侵蚀和沟底下切侵蚀三种侵蚀模式分别作为纵向、横向和纵向维度的代表因子。通过这些因素，揭示了沟顶侵蚀过程中三种截然不同的优势发育模式的特征模式。结果表明：(1)流量显著影响沟长和沟宽的变化，使平均头沟退缩侵蚀率和平均头沟侵蚀宽度分别增加了至少19.5%和10.4%；沟顶高度显著影响沟底切口深度，使沟底平均高程降低至少21.0%。(2)离坡顶越远，沟壁塌陷引起的沟宽越大，坡上、坡中、坡下塌陷的平均宽度分别为0.9、1.9、3.8 cm，说明坡下更容易发生滑坡。(3)沟底坡度随沟头高度的增加而增大。随着流量的增加，沟底坡面形态由“上凸”向“下凹”转变。(4)在侵蚀发育早期，以顶切退缩侵蚀为主，占产沙总量的53.2% ~ 82.7%。中后期以沟壁膨胀和沟底侵蚀沉积为主。这些研究结果为黄土斜坡沟壑区侵蚀机理的研究提供了新的思路。
{"title":"Quantification of Erosion Development Patterns Based on the Gully Headcut Erosion","authors":"Wang Rui, Li Peng, Zhang Peidong, Zheng Xiaofeng, Liang Jichao, Han Jianchun, Cui Zhiwei","doi":"10.1002/ldr.70153","DOIUrl":"https://doi.org/10.1002/ldr.70153","url":null,"abstract":"The study of mechanisms of gully headcut erosion is crucial for predicting and preventing soil erosion and effectively reducing gully erosion. However, quantitative analysis from multiple perspectives and dimensions of gully morphological characteristics and their evolution patterns is still unclear. This study conducted a series of indoor flushing experiments using gully headcuts of different heights (flow rates of 2, 4, and 6 L min <jats:sup>−1</jats:sup> ; gully headcut heights of 5, 10, and 15 cm). Based on DEM and monitoring data, this study utilizes three erosion modes: gully headcut retreat erosion, gully wall widening erosion, and gully bed downcutting erosion, as representative factors for the longitudinal, lateral, and vertical dimensions, respectively. Through these factors, the characteristic patterns of three distinct dominant developmental modes during gully headcut erosion are revealed. The results indicate that: (1) Discharge rate significantly impacts changes in gully length and width, increasing average headcut retreat erosion rates by at least 19.5% and average headcut erosion width by at least 10.4%. Gully headcut height notably affects gully bottom incision depth, reducing average gully bottom elevation by at least 21.0%. (2) The farther away from the top of the slope, the larger the width of the gully caused by the collapse of the gully wall, and the average widths of the collapse on the slope, during the slope and under the slope were 0.9, 1.9, and 3.8 cm, respectively, indicating that the collapse of the slope is more likely to occur under the slope. (3) The slope of the gully bottom increases with the height of the gully headcut. As the discharge increases, the morphology of the gully bottom slope transitions from “convex upwards” to “concave downwards”. (4) In early stages of erosion development, headcut retreat erosion predominates, contributing 53.2%–82.7% of sediment production. In middle and later stages, gully wall expansion and gully bottom erosion and deposition dominate. These research findings provide insights into mechanisms governing gully erosion on loess slopes.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"21 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The conversion of Chinese farmland to non‐main grain cropland (NMGL) threatens national food security, yet its local‐scale dynamics remain poorly understood. Here, we provide a county‐level analysis of the spatiotemporal patterns and drivers of this land‐use change. We identify striking regional disparities: the prevalence of NMGL is highest in major grain consumption areas (22.3%), intermediate in balanced zones (18.4%), and lowest in production areas (11.6%). Between 1985 and 2020, this trend evolved from localized occurrences into a widespread phenomenon. Crop systems influence conversion risks, with single‐cropping systems exhibiting a 2.1–3.8 times higher vulnerability to conversion than intercropped systems. Driver analysis indicates that soil factors (particularly organic carbon) are the primary determinant nationwide (40% contribution), although socioeconomic factors prevail in balanced regions. To effectively preserve China's agricultural land, management frameworks need transition from rigid regulation of non‑grain cropping areas toward a dynamic protection strategy anchored in food‑balance demands. A smarter, system‐wide approach is needed that optimizes planting structures and agricultural layouts. Our study provides critical insights for formulating a food balance demand‐oriented farmland protection strategy.
{"title":"Revealing the Process and Mechanism of Non‐Main Grain Cropland Expansion in China","authors":"Jie Zhang, Shidong Liu","doi":"10.1002/ldr.70384","DOIUrl":"https://doi.org/10.1002/ldr.70384","url":null,"abstract":"The conversion of Chinese farmland to non‐main grain cropland (NMGL) threatens national food security, yet its local‐scale dynamics remain poorly understood. Here, we provide a county‐level analysis of the spatiotemporal patterns and drivers of this land‐use change. We identify striking regional disparities: the prevalence of NMGL is highest in major grain consumption areas (22.3%), intermediate in balanced zones (18.4%), and lowest in production areas (11.6%). Between 1985 and 2020, this trend evolved from localized occurrences into a widespread phenomenon. Crop systems influence conversion risks, with single‐cropping systems exhibiting a 2.1–3.8 times higher vulnerability to conversion than intercropped systems. Driver analysis indicates that soil factors (particularly organic carbon) are the primary determinant nationwide (40% contribution), although socioeconomic factors prevail in balanced regions. To effectively preserve China's agricultural land, management frameworks need transition from rigid regulation of non‑grain cropping areas toward a dynamic protection strategy anchored in food‑balance demands. A smarter, system‐wide approach is needed that optimizes planting structures and agricultural layouts. Our study provides critical insights for formulating a food balance demand‐oriented farmland protection strategy.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"30 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a vital component of the land–atmosphere interaction system, soil moisture plays an indispensable role. In arid and semi‐arid regions, soil moisture serves as a key indicator of ecosystem vulnerability and also functions as an essential role in drought monitoring, climate research, agricultural water resource management, and land management. This study integrates radar and optical remote sensing data combined with intelligent algorithms based on machine learning to construct and evaluate soil moisture estimation frameworks across diverse data combinations. The Yutian Oasis was selected as the study area, and four hybrid models (ACO‐RF, ACO‐SVM, SSA‐RF, and SSA‐SVM) were developed by optimizing standalone random forest (RF) and support vector machine (SVM) models using ant colony optimization (ACO) and sparrow search algorithm (SSA). Three different combinations of input data sources were constructed based on GF‐3 and Sentinel‐2 data. A total of six models were employed to assess soil moisture throughout the study area under three different data source scenarios. The results indicated that compared to the other two single‐source datasets, all models achieved the highest prediction accuracy when using the GF‐3 + Sentinel‐2 datasets. Specifically, the ACO‐RF model exhibited superior results, with R2 values in the test set improved by 9.59% and 5.26% compared to models using GF‐3 or Sentinel‐2 data alone, respectively. Across all models, the four hybrid models outperformed the standalone RF and SVM models. Among the hybrid models, ACO‐RF demonstrated the best overall outcomes, achieving an R2 of 0.80, RMSE of 3.07%, and RPD of 2.30. Therefore, integrating radar and optical data with intelligent algorithm‐optimized machine learning strategies improves soil moisture estimation precision, offering significant support for sustainable oasis agriculture and land management in arid regions.
{"title":"Synergistic Retrieval of Soil Moisture in Arid Regions Using GF ‐3 SAR and Sentinel‐2 Optical Data","authors":"Yu Qin, Ilyas Nurmemet, Aihepa Aihaiti, Xinru Yu, Yilizhati Aili, Xiaobo Lv, Shiqin Li","doi":"10.1002/ldr.70373","DOIUrl":"https://doi.org/10.1002/ldr.70373","url":null,"abstract":"As a vital component of the land–atmosphere interaction system, soil moisture plays an indispensable role. In arid and semi‐arid regions, soil moisture serves as a key indicator of ecosystem vulnerability and also functions as an essential role in drought monitoring, climate research, agricultural water resource management, and land management. This study integrates radar and optical remote sensing data combined with intelligent algorithms based on machine learning to construct and evaluate soil moisture estimation frameworks across diverse data combinations. The Yutian Oasis was selected as the study area, and four hybrid models (ACO‐RF, ACO‐SVM, SSA‐RF, and SSA‐SVM) were developed by optimizing standalone random forest (RF) and support vector machine (SVM) models using ant colony optimization (ACO) and sparrow search algorithm (SSA). Three different combinations of input data sources were constructed based on GF‐3 and Sentinel‐2 data. A total of six models were employed to assess soil moisture throughout the study area under three different data source scenarios. The results indicated that compared to the other two single‐source datasets, all models achieved the highest prediction accuracy when using the GF‐3 + Sentinel‐2 datasets. Specifically, the ACO‐RF model exhibited superior results, with <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> values in the test set improved by 9.59% and 5.26% compared to models using GF‐3 or Sentinel‐2 data alone, respectively. Across all models, the four hybrid models outperformed the standalone RF and SVM models. Among the hybrid models, ACO‐RF demonstrated the best overall outcomes, achieving an <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> of 0.80, RMSE of 3.07%, and RPD of 2.30. Therefore, integrating radar and optical data with intelligent algorithm‐optimized machine learning strategies improves soil moisture estimation precision, offering significant support for sustainable oasis agriculture and land management in arid regions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"370 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The application rate and droplet characteristics of sprinkler irrigation influence soil erosion and nitrogen loss. Canopy cover significantly alters the application rate and droplet characteristics. However, limited information is available on how sprinkler irrigation affects soil runoff, erosion, and nitrogen loss under canopy cover, especially under fertigation conditions. This study uses Nelson R33 sprinklers for indoor soil tank experiments to investigate the effects of maize canopy, application rate, and soil slope on the runoff occurrence time, steady runoff rate, cumulative soil loss, and nitrogen loss from silty clay loam soils during sprinkler irrigation. The results indicate that canopy cover clearly reduces surface runoff velocity and soil loss. Runoff rates increased with slope under high application rates but decreased under lower application rates. The higher the application rate, kinetic energy, and specific power, the shorter the runoff occurrence time, the larger the steady runoff velocity, and the greater the soil loss. Both NO 3− and NH 4+ loss rates in the runoff and sediments increased with increasing application rate and soil slope. Nitrogen in calcium ammonium nitrate fertilizers in the runoff was lost mainly as NO 3− . During the sprinkler irrigation period, although canopy cover increased nitrogen concentration in the runoff and sediment, canopy cover decreased sprinkler intensity, thereby reducing runoff rate. This reduces the nitrate loss rate under canopy cover by 0.03–0.88 times. When designing a sprinkler irrigation system, it is necessary to select an appropriate sprinkler application rate and irrigation duration to minimize soil erosion as much as possible.
{"title":"The Effect of the Maize Canopy on Soil Erosion and Nitrogen Loss Processes Under Sprinkler Irrigation and Fertigation","authors":"Yu Xiang, Rui Chen, Jian Wang, Xin Guo, Hong Li","doi":"10.1002/ldr.70382","DOIUrl":"https://doi.org/10.1002/ldr.70382","url":null,"abstract":"The application rate and droplet characteristics of sprinkler irrigation influence soil erosion and nitrogen loss. Canopy cover significantly alters the application rate and droplet characteristics. However, limited information is available on how sprinkler irrigation affects soil runoff, erosion, and nitrogen loss under canopy cover, especially under fertigation conditions. This study uses Nelson R33 sprinklers for indoor soil tank experiments to investigate the effects of maize canopy, application rate, and soil slope on the runoff occurrence time, steady runoff rate, cumulative soil loss, and nitrogen loss from silty clay loam soils during sprinkler irrigation. The results indicate that canopy cover clearly reduces surface runoff velocity and soil loss. Runoff rates increased with slope under high application rates but decreased under lower application rates. The higher the application rate, kinetic energy, and specific power, the shorter the runoff occurrence time, the larger the steady runoff velocity, and the greater the soil loss. Both NO <jats:sub>3</jats:sub> <jats:sup>−</jats:sup> and NH <jats:sub>4</jats:sub> <jats:sup>+</jats:sup> loss rates in the runoff and sediments increased with increasing application rate and soil slope. Nitrogen in calcium ammonium nitrate fertilizers in the runoff was lost mainly as NO <jats:sub>3</jats:sub> <jats:sup>−</jats:sup> . During the sprinkler irrigation period, although canopy cover increased nitrogen concentration in the runoff and sediment, canopy cover decreased sprinkler intensity, thereby reducing runoff rate. This reduces the nitrate loss rate under canopy cover by 0.03–0.88 times. When designing a sprinkler irrigation system, it is necessary to select an appropriate sprinkler application rate and irrigation duration to minimize soil erosion as much as possible.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"117 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farmland abandonment is a common phenomenon that occurs at a certain stage of rural economic development and is a dynamic process driven by multiple factors. Investigating the interactions among multiple factors influencing regional farmland abandonment across spatial and temporal dimensions is crucial for formulating reclamation policies and ensuring food security Therefore, this study develops an analytical framework for factors influencing farmland abandonment based on configuration theory. Taking 13 districts (counties) in the Huangshui Basin from 2002 to 2020 as case samples, this study applies a dynamic qualitative comparative analysis (QCA) to explore the configuration effects of these factors on farmland abandonment over the time series. The results indicate that no single condition constitutes a necessary condition for farmland abandonment; however, the necessity of geographical environmental conditions shows a steadily increasing trend over the study period. In the sufficiency analysis of configurations leading to a high farmland abandonment index, five configuration paths were identified, categorized into three types: environment‐driven, population–resource constrained, and population–economy–policy deficient. Three additional configuration paths were found for non‐high abandonment, categorized as population‐oriented and economy‐driven. These findings provide a new perspective for analyzing the factors influencing farmland abandonment in both temporal and spatial dimensions, and also offer a theoretical foundation and data support for the reuse of abandoned farmland.
{"title":"Empirical Analysis on the Influencing Factors of Farmland Abandonment From the Perspective of Complex Configuration","authors":"Juan Wang, Hongyu Wang, Rongrong Ma, Wei Zhou","doi":"10.1002/ldr.70304","DOIUrl":"https://doi.org/10.1002/ldr.70304","url":null,"abstract":"Farmland abandonment is a common phenomenon that occurs at a certain stage of rural economic development and is a dynamic process driven by multiple factors. Investigating the interactions among multiple factors influencing regional farmland abandonment across spatial and temporal dimensions is crucial for formulating reclamation policies and ensuring food security Therefore, this study develops an analytical framework for factors influencing farmland abandonment based on configuration theory. Taking 13 districts (counties) in the Huangshui Basin from 2002 to 2020 as case samples, this study applies a dynamic qualitative comparative analysis (QCA) to explore the configuration effects of these factors on farmland abandonment over the time series. The results indicate that no single condition constitutes a necessary condition for farmland abandonment; however, the necessity of geographical environmental conditions shows a steadily increasing trend over the study period. In the sufficiency analysis of configurations leading to a high farmland abandonment index, five configuration paths were identified, categorized into three types: environment‐driven, population–resource constrained, and population–economy–policy deficient. Three additional configuration paths were found for non‐high abandonment, categorized as population‐oriented and economy‐driven. These findings provide a new perspective for analyzing the factors influencing farmland abandonment in both temporal and spatial dimensions, and also offer a theoretical foundation and data support for the reuse of abandoned farmland.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"56 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ecological environmental quality (EEQ) directly influences public health, resource availability, and climate resilience for national ecological security and sustainable development. Urban agglomerations experience growing ecological stress under rapid urbanization, yet integrated assessments of EEQ dynamics remain limited. This study develops a Novel Remote Sensing Ecological Index (NRSEI) on the Google Earth Engine (GEE) platform by integrating multi‐source datasets, including Landsat imagery and NPP–VIIRS nighttime light data. The Yangtze River Delta Urban Agglomeration (YRDUA) is selected as the study area to analyze long‐term variations in EEQ. The NRSEI integrates five core indicators, namely vegetation greenness, surface wetness, land surface temperature, air pollution represented by PM 2.5 , and human activity intensity, providing a comprehensive assessment of EEQ. Results from 2003 to 2023 reveal an “N‐shaped” temporal pattern: slight improvement (2003–2008), decline (2008–2018), and moderate recovery (2018–2023). Spatially, EEQ exhibits a clear northwest–southeast gradient, with lower values in industrial–agricultural zones and higher values in mountainous and coastal areas. Geographical Detector analysis identifies elevation, mean temperature, and economic development as dominant drivers of EEQ heterogeneity, with synergistic effects exceeding individual influences. Overall, this study establishes a refined and scalable framework for long‐term, high‐resolution ecological monitoring and provides empirical evidence to guide balanced urban and ecological development in rapidly urbanizing regions.
{"title":"Urban Ecological Resilience and Transitions in the Yangtze River Delta: Insights From Remote Sensing Analytics","authors":"Lifu Chai, Huiming Ke, Yuehao Li, Su Zhang, Chen Cao, Xiaoyi Wang, Mingjie Xu, Zongmei Chen, Yanfei Wang, Lifeng Zhang","doi":"10.1002/ldr.70375","DOIUrl":"https://doi.org/10.1002/ldr.70375","url":null,"abstract":"Ecological environmental quality (EEQ) directly influences public health, resource availability, and climate resilience for national ecological security and sustainable development. Urban agglomerations experience growing ecological stress under rapid urbanization, yet integrated assessments of EEQ dynamics remain limited. This study develops a Novel Remote Sensing Ecological Index (NRSEI) on the Google Earth Engine (GEE) platform by integrating multi‐source datasets, including Landsat imagery and NPP–VIIRS nighttime light data. The Yangtze River Delta Urban Agglomeration (YRDUA) is selected as the study area to analyze long‐term variations in EEQ. The NRSEI integrates five core indicators, namely vegetation greenness, surface wetness, land surface temperature, air pollution represented by PM <jats:sub>2.5</jats:sub> , and human activity intensity, providing a comprehensive assessment of EEQ. Results from 2003 to 2023 reveal an “N‐shaped” temporal pattern: slight improvement (2003–2008), decline (2008–2018), and moderate recovery (2018–2023). Spatially, EEQ exhibits a clear northwest–southeast gradient, with lower values in industrial–agricultural zones and higher values in mountainous and coastal areas. Geographical Detector analysis identifies elevation, mean temperature, and economic development as dominant drivers of EEQ heterogeneity, with synergistic effects exceeding individual influences. Overall, this study establishes a refined and scalable framework for long‐term, high‐resolution ecological monitoring and provides empirical evidence to guide balanced urban and ecological development in rapidly urbanizing regions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"64 3 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bin Zhang, Haoran Zeng, Haijun Wang, Jianxin Yang, Zhaomin Tong, Shougeng Hu
Capturing patch features can significantly enhance the performance of cellular automata (CA)‐based land use modeling. However, current research has yet to comprehensively explore the definition of patch‐based CA simulation rules and their integration with grid‐based rules. This study proposes a generalized urban CA framework that integrates grid‐ and patch‐based rules across scales. Using Beijing's urban growth from 2000 to 2020 as a case study, we evaluated the simulation performance of CA under different rule‐integration modes. The results demonstrate that patch‐level assessment of urban growth potential improves the model's temporal generalizability, robustness, and accuracy. However, using patches as cells for local interactions reduces simulation performance and efficiency, whereas grid‐based neighborhoods produce better results by more closely resembling complex boundary buffer neighborhoods. Furthermore, treating patches as basic units for urban expansion control enhances simulated urban morphology and accuracy. Integrating these optimal rules across scales within the proposed framework yields the best‐performing CA model. This study offers a methodological reference for grid‐patch integration in land use modeling, which can facilitate pre‐assessing urban growth‐induced land degradation risks and achieving reasonable spatial planning, supporting sustainable urban development.
{"title":"Grid, Patch, or Multi‐Scale Integration? A Comparative Analysis for Cellular Automata‐Based Urban Growth Simulations","authors":"Bin Zhang, Haoran Zeng, Haijun Wang, Jianxin Yang, Zhaomin Tong, Shougeng Hu","doi":"10.1002/ldr.70374","DOIUrl":"https://doi.org/10.1002/ldr.70374","url":null,"abstract":"Capturing patch features can significantly enhance the performance of cellular automata (CA)‐based land use modeling. However, current research has yet to comprehensively explore the definition of patch‐based CA simulation rules and their integration with grid‐based rules. This study proposes a generalized urban CA framework that integrates grid‐ and patch‐based rules across scales. Using Beijing's urban growth from 2000 to 2020 as a case study, we evaluated the simulation performance of CA under different rule‐integration modes. The results demonstrate that patch‐level assessment of urban growth potential improves the model's temporal generalizability, robustness, and accuracy. However, using patches as cells for local interactions reduces simulation performance and efficiency, whereas grid‐based neighborhoods produce better results by more closely resembling complex boundary buffer neighborhoods. Furthermore, treating patches as basic units for urban expansion control enhances simulated urban morphology and accuracy. Integrating these optimal rules across scales within the proposed framework yields the best‐performing CA model. This study offers a methodological reference for grid‐patch integration in land use modeling, which can facilitate pre‐assessing urban growth‐induced land degradation risks and achieving reasonable spatial planning, supporting sustainable urban development.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"7 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Soil bacterial communities, which are vital for nutrient cycling and fertility, may experience intensified alterations under forest‐to‐orchard conversions in the acidic, nutrient‐deficient red‐soil hills of southern China, yet the long‐term impacts of such changes remain poorly understood. This study investigated the effects of forest‐to‐orchard land use conversion and prolonged orchard cultivation (9 and 16 years) on soil nutrient dynamics and bacterial community structure in a subtropical red soil hilly region of southern China. The soil physicochemical properties, bacterial community compositions, co‐occurrence network, and predicted metabolic pathways were analyzed to assess microbial responses. Land use conversion from forestland to a 16‐year orchard markedly enhanced soil nutrient availability, with soil organic matter increasing from 16.09 g·kg −1 in forest soil to 21.92 g·kg −1 in the soil of the 16‐year‐old orchard and the available phosphorus concentration increasing from 45.87 mg·kg −1 to 298.96 mg·kg −1 , indicating substantial nutrient enrichment under orchard cultivation. Orchard establishment also shifted the bacterial community composition, with the abundance of Proteobacteria increasing and that of Acidobacteriota decreasing. Co‐occurrence network analysis revealed initially more complex microbial interactions in orchard soils, including the emergence of Verrucomicrobiota taxa that were absent from forest soils, but the network complexity declined after 16 years of cultivation. Soil organic matter and available phosphorus were key drivers of the changes in community structure. The predicted functional profiles indicated a clear metabolic shift from nutrient‐conserving pathways (e.g., organic nitrogen degradation prevalent in forest soils) to enhanced biosynthesis and fermentation pathways in orchard soils. This shift reflected a transition in microbial strategy from resource‐conserving to rapid cycling under prolonged cultivation. Overall, these findings highlight the strong influence of land use conversion and soil nutrient status on microbial community assembly and function, and underscored the need for nutrient‐sensitive management to sustain soil health and ecosystem services in orchard systems. These insights offer an ecological guide for optimizing fertilization and organic‐matter management to improve soil resilience and sustain the productivity of red‐soil hilly orchards converted from forests.
{"title":"Impact of Land Use Conversion on Soil Environmental Factors and Bacterial Community Composition in the Red Soil Hilly Region of Southern China","authors":"Zuopin Zhuo, Bangning Zhou, Heming Li, Chuanjin Xie, Xiaopeng Wang, Fangshi Jiang, Jinshi Lin, Yanhe Huang, Yue Zhang","doi":"10.1002/ldr.70361","DOIUrl":"https://doi.org/10.1002/ldr.70361","url":null,"abstract":"Soil bacterial communities, which are vital for nutrient cycling and fertility, may experience intensified alterations under forest‐to‐orchard conversions in the acidic, nutrient‐deficient red‐soil hills of southern China, yet the long‐term impacts of such changes remain poorly understood. This study investigated the effects of forest‐to‐orchard land use conversion and prolonged orchard cultivation (9 and 16 years) on soil nutrient dynamics and bacterial community structure in a subtropical red soil hilly region of southern China. The soil physicochemical properties, bacterial community compositions, co‐occurrence network, and predicted metabolic pathways were analyzed to assess microbial responses. Land use conversion from forestland to a 16‐year orchard markedly enhanced soil nutrient availability, with soil organic matter increasing from 16.09 g·kg <jats:sup>−1</jats:sup> in forest soil to 21.92 g·kg <jats:sup>−1</jats:sup> in the soil of the 16‐year‐old orchard and the available phosphorus concentration increasing from 45.87 mg·kg <jats:sup>−1</jats:sup> to 298.96 mg·kg <jats:sup>−1</jats:sup> , indicating substantial nutrient enrichment under orchard cultivation. Orchard establishment also shifted the bacterial community composition, with the abundance of Proteobacteria increasing and that of Acidobacteriota decreasing. Co‐occurrence network analysis revealed initially more complex microbial interactions in orchard soils, including the emergence of Verrucomicrobiota taxa that were absent from forest soils, but the network complexity declined after 16 years of cultivation. Soil organic matter and available phosphorus were key drivers of the changes in community structure. The predicted functional profiles indicated a clear metabolic shift from nutrient‐conserving pathways (e.g., organic nitrogen degradation prevalent in forest soils) to enhanced biosynthesis and fermentation pathways in orchard soils. This shift reflected a transition in microbial strategy from resource‐conserving to rapid cycling under prolonged cultivation. Overall, these findings highlight the strong influence of land use conversion and soil nutrient status on microbial community assembly and function, and underscored the need for nutrient‐sensitive management to sustain soil health and ecosystem services in orchard systems. These insights offer an ecological guide for optimizing fertilization and organic‐matter management to improve soil resilience and sustain the productivity of red‐soil hilly orchards converted from forests.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"7 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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